At a Glance
- Tasks: Lead AI infrastructure strategy and architect scalable solutions for cutting-edge AI workloads.
- Company: Join Lenovo, a global tech powerhouse transforming the future with smarter technology.
- Benefits: Enjoy a hybrid working model, discounts on products, and a positive work-life balance.
- Other info: Be part of a diverse team driving world-changing innovation and career growth.
- Why this job: Shape AI at a global scale and make a real impact in an innovative environment.
- Qualifications: 12+ years in software or infrastructure engineering, with expertise in AI/ML infrastructure.
The predicted salary is between 81000 - 99000 £ per year.
We are Lenovo. We do what we say. We own what we do. We WOW our customers.
Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets.
Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services.
Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere.
Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit
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Description and Requirements
The Advanced AI Technology Center (AAITC)—Lenovo’s global AI Center of Excellence is driving our transformation into an AI-first organization.
We are assembling a world-class team of researchers, engineers, and innovators to position Lenovo and its customers at the forefront of the generational shift toward AI.
We are building the next wave of AI core technologies and platforms that leverage and evolve with the fast-moving AI ecosystem, including novel model and agentic orchestration & collaboration across mobile, edge, and cloud resources.
This space is evolving fast and so are we.
If you’re ready to shape AI at a truly global scale, with products that touch every corner of life and work, there’s no better time to join us. #LATC
Responsibilities
- AI Infrastructure Strategy and
Architecture: Define and drive the long-term infrastructure strategy for AI workloads.
Architect scalable, cost-efficient, and resilient compute, storage, and networking solutions that support the full AI lifecycle from experimentation through production.
- Technical Leadership and
Mentorship: Serve as a technical lead and mentor to infrastructure engineers, establishing engineering standards, conducting design reviews, and fostering a culture of operational excellence across the team.
- AI Model Deployment and
- Platform
Engineering: Design and own the platforms, frameworks, and processes for deploying, monitoring, and managing AI models at scale in production environments, including model serving, A/B testing infrastructure, and rollback mechanisms.
- Advanced Automation and CI/CD: Architect and maintain sophisticated automation pipelines for AI model training, evaluation, testing, and deployment.
Champion infrastructure-as-code practices and drive continuous improvement of CI/CD workflows.
- Cross-Functional
Collaboration: Partner with data scientists, ML engineers, product managers, and leadership to align infrastructure capabilities with research and business objectives.
Act as the primary infrastructure point of contact for cross-team initiatives.
- Performance
Engineering: Lead efforts to profile, benchmark, and optimize AI infrastructure and model serving for throughput, latency, GPU utilization, scalability, and cost efficiency at scale.
- Security, Compliance, and
Governance: Establish and enforce security best practices, access controls, and compliance frameworks across AI infrastructure.
Ensure adherence to relevant regulatory requirements and internal governance policies.
- Capacity Planning and
- Cost
Management: Own capacity forecasting, resource planning, and cost optimization for GPU clusters and associated infrastructure, balancing performance needs with budget constraints.
Qualifications
- Bachelor’s or Master’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field. Advanced degree preferred.
- 12+ years of experience in software engineering, infrastructure engineering, Dev Ops/SRE, or a related field, with at least 4 years focused on AI/ML infrastructure.
- Demonstrated experience leading or mentoring engineering teams on infrastructure projects.
- Deep expertise in computer systems, distributed systems, and cloud computing architectures.
- Strong proficiency in Python and at least one additional systems language (e. g., Go, C++, Rust, Java) as well as understanding of Design Patterns and Solution Architecture.
- Expert-level Linux system administration, including package management, user/group management, file system internals, shell scripting (e. g., Bash), networking, and system configuration (e. g., systemd, kernel tuning).
- Strong architectural thinking with the ability to balance trade-offs across performance, reliability, security, and cost.
- Excellent communication and collaboration skills, with the ability to influence technical decisions across teams and present to senior leadership.
- Ability to thrive in a fast-paced, ambiguous environment and drive clarity through technical leadership.
- Expertise with observability stacks (e. g., Prometheus, Grafana, ELK/Open Search, Datadog) for infrastructure, open telemetry n-tier application stacks and model monitoring with open telemetry and open inference.
- Knowledge of observability stacks, open
- Bonus Points
- Experience with AI and machine learning frameworks at scale (e. g., Py Torch, Deep Speed, Megatron-LM, v LLM).
- Hands-on experience with major cloud platforms (e. g., AWS, GCP, Azure) and hybrid cloud architectures.
- Advanced experience with containerization (Docker) and orchestration (Kubernetes), including custom operators, Helm charts, and GPU scheduling plugins.
- Expertise with observability stacks (e. g., Prometheus, Grafana, ELK/Open Search, Datadog) for infrastructure and model monitoring.
- Experience with infrastructure-as-code tools (e. g., Terraform, Ansible, Pulumi).
- Contributions to open-source infrastructure or ML tooling projects.
- Experience with large language model (LLM) training and inference infrastructure.
What we can offer you
- Hybrid working model (3:2)
- Positive work life balance
- Learning and development
- Lenovo and Motorola products discounts
- Cycle to work
- Mortgage advice and support
We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.
- Additional Locations
- United Kingdom
- AI PROCESSING NOTICE
We use AI-based tools to support some of our processes (e. g. online interviews recordings and transcripts) in order to achieve better efficiency, accuracy and for our documentation purposes.
AI can make mistakes, but we always make sure that the outputs are manually reviewed by a human.
You can always opt-out or contact us in case of any question.
- If you require an accommodation to complete this application, please contact
- #J-18808-Ljbffr
Sr. AI Engineer (Platform Infrastructure) in London employer: Lenovo Inc.
Lenovo Inc. offers a vibrant work culture that emphasizes innovation and customer satisfaction. Employees benefit from numerous professional development opportunities and a commitment to diversity and inclusion. The company's focus on cutting-edge technology ensures a stimulating environment for career growth.
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We think you need these skills to ace Sr. AI Engineer (Platform Infrastructure) in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
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How to prepare for a job interview at Lenovo Inc.
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Lenovo Inc. uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
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While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.